Huiping Si

Papers

Total Citations

H-Index

About

Huiping Si’s research lies at the intersection of computer vision, robotics, and autonomous systems, with a particular focus on 3D perception and intelligent navigation. Her most cited work, “A Survey on Monocular 3D Object Detection Algorithms Based on Deep Learning” (2020), has garnered 20 citations and provides a comprehensive taxonomy of deep learning methods for estimating object location and pose from a single camera—a critical capability for cost-effective autonomous driving and robotics. This survey systematically categorizes algorithms by their architectural approaches, offering researchers a clear roadmap for advancing monocular 3D detection. Si also explores the practical application of computer vision in agriculture, as seen in her review on fruit-picking robots (4 citations), where she analyzes vision-guided grasping for automated harvesting. Earlier work on complete coverage path planning and obstacle avoidance (2012, 2 citations) demonstrates her foundational contributions to mobile robot navigation, proposing integrated strategies for efficient traversal and collision-free movement. By bridging theoretical algorithm design with real-world robotic applications—from autonomous vehicles to agricultural robots—Si’s work provides essential guidance for students and engineers developing perception and planning systems for intelligent machines.